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In this paper I present a Minimum Description Length Estimator for number of sources in an anechoic mixture of sparse signals.The criterion is roughly equal to the sum of negative normalized maximum l...
In this paper we present an Information Theoretic Estimator for the number of sources mutuallydisjoint in a linear mixing model. The approach follows the Minimum Description Length prescription and is...
Many tasks (e.g., clustering) in machine learning only require the lα distances instead of the original data. For dimension reductions in the lα norm (0 < α ≤ 2), the method of stable random projectio...
This note is a discussion of the paper "Confidence distribution" by Min-ge Xie and Kesar Singh, to appear in the International Statistical Review.
Various data analyses of the Cosmic Microwave Background (CMB) provide observational hints of statistical isotropy breaking. Some of these features can be studied within the framework of primordial ve...
This paper is first devoted to study an adaptive wavelet based estimator of the long memory parameter for linear processes in a general semi-parametric frame. This is an extension of Bardet et al. (20...
Models of the Universe like the Concordance Model today used to interpret cosmological observations give expectation values for many cosmological observable so accurate that frequently peoples speak o...
We consider some (anisotropic and piecewise constant) convection-diffusion-reaction problems in domains of R2, approximated by a discontinuous Galerkin method with polynomials of any degree. We propos...
This paper addresses the estimation of locally stationary long-range dependent processes, a methodology that allows the statistical analysis of time series data exhibiting both nonstationarity and str...
The electrical power network is a critical infrastructure in today's society, so its safe and reliable operation is of major concern. State estimators are commonly used in power networks, for example,...
The problem of estimating the tail index from truncated data is addressed in Chakrabarty and Samorodnitsky (2009). In that paper, a sample based (and hence random) choice of k is uggested,and it is sh...
We study the performance of estimators of a sparse nonrandom vector based on an observation which is linearly transformed and corrupted by additive white Gaussian noise.
This paper considers a simulation-based estimator for a general class of Markovian processes and explores some strong consistency properties of the estimator. The estimation problem is defined over a ...
Various statistical methods are used to process operational Numerical Weather Prediction (NWP) products with the aim of reducing forecast errors and they often require sufficiently large training data...
Robust impedance estimation procedures are now in standard use in magnetotelluric (MT) measurements and research. These always yield impedance estimates which are better than the conventional least sq...

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